Video conversation models are multimodal artificial intelligence systems designed to interpret video inputs and engage in interactive, natural language dialogue about their visual and temporal content. Typically built by integrating spatiotemporal video encoders with large language models, these systems process sequential frames and temporal dynamics to comprehend actions, scene transitions, and complex events over time. Unlike static image-dialogue systems, video conversation models track contextual changes across dynamic scenes, enabling users to ask questions, request summaries, and hold coherent, multi-turn conversations directly grounded in video data.
